Magnetoencephalography as a tool in psychiatric research: current status and perspective

The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. In this review, we propose that recent technological and analytic advances in Magnetoencephalography (MEG), a technique which allows the measurement of neuronal events directly and non-invasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as Schizophrenia, Autism Spectrum Disorders, and the dementias. In our paper, we summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then survey recent studies that have utilized MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This is followed by links with preclinical research, which have highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, which could account for measured changes in neural oscillations. In the final section of the paper, challenges as well as novel methodological developments are discussed which could pave the way for a widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis

Evaluating Social Innovation

The philanthropic sector has been experimenting with innovative grantmaking in the hopes of triggering significant and sustainable change. FSG's latest research report, collaboratively written with the Center for Evaluation Innovation, challenges grantmakers to explore the use of Developmental Evaluation when evaluating complex, dynamic, and emergent initiatives

Integrating EEG and MEG signals to improve motor imagery classification in brain-computer interfaces

We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification performances in motor imagery-based brain-computer interfaces (BCIs). We applied our approach to a group of 15 healthy subjects and found a significant classification performance enhancement as compared to standard single-modality approaches in the alpha and beta bands. Taken together, our findings demonstrate the advantage of considering multimodal approaches as complementary tools for improving the impact of non-invasive BCIs

Victorian Women's Trust, Annual Report 2010/2011

We are an independent advocate for women and grant maker dedicated to improving the status of women and girls. We are now among the world's oldest women's funds, and pride ourselves on a thirty-year tradition of progressive philanthropy, strategically targeted to maximise our impact across the range of issues we seek to address - violence against women and girls, gendered discrimination and disadvantage, the quest for due recognition of the value of women's paid and unpaid work, and towards equal representation in the decision making processes that shape our lives

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity

Objective. Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. Approach. A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. Main results. The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. Significance. The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.Postprint (published version

Beyond Tutoring: Mapping The Invisible Landscape of Writing Center Work

In their call for papers for this special issue of Praxis, the editors speculate that most writing centers assume various roles beyond those implied by the triage model of fix-it consultations. We agree. As the call suggests, writing centers have long sought to “carve out a broader purview” for themselves—to extend writing center efforts both beyond the center’s physical space and beyond enduring writing center master narratives about the primacy of individual instruction. Still, much of the writing center’s extra curriculum, or what we call here non-tutoring work, remains hidden: for example, writing center scholarship provides anecdotal evidence of writing centers’ work with faculty, but the scholarship rarely tells us just how prevalent such efforts are across the board or what other kinds of non-tutoring work we are engaged in. To borrow from the field of landscape architecture, what our field lacks is an aerial—and ultimately generative—vision of our non-tutoring activities, one that would “reveal aspects of the landscape that are invisible from the ground and offer an alternative to pictorial [read “local”] practices so common in landscape representation” (Czerniak 111). There are consequences to invisibility. We cannot theorize what we cannot see, although theories are always already there, shaping our identities and practices in ways that might or might not be acceptable to us if only we could see and name their contours. Viewing the writing center landscape from a different vantage point, then, gives us much more than an updated map: it challenges us to re-theorize who we are and what makes our work valuable.University Writing Cente

Language Assessment for School-aged Children: Examining the Evidence and Describing Clinical Practice

Accurate speech-language pathology assessment is vital for determining the intervention needs of children with language disorders. This thesis investigated research evidence in relation to language assessment practices for school-aged children. Consensus on terminology for describing assessments was obtained and current language assessment practices were examined to identify actions to help improve speech-language pathologist’s implementation of evidence-based practice recommendations. Information gained from this thesis will assist with enhancing service provision for school-aged children with language disorders

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity

Gating of memory encoding of time-delayed cross-frequency MEG networks revealed by graph filtration based on persistent homology

To explain gating of memory encoding, magnetoencephalography (MEG) was analyzed over multi-regional network of negative correlations between alpha band power during cue (cue-alpha) and gamma band power during item presentation (item-gamma) in Remember (R) and No-remember (NR) condition. Persistent homology with graph filtration on alpha-gamma correlation disclosed topological invariants to explain memory gating. Instruction compliance (R-hits minus NR-hits) was significantly related to negative coupling between the left superior occipital (cue-alpha) and the left dorsolateral superior frontal gyri (item-gamma) on permutation test, where the coupling was stronger in R than NR. In good memory performers (R-hits minus false alarm), the coupling was stronger in R than NR between the right posterior cingulate (cue-alpha) and the left fusiform gyri (item-gamma). Gating of memory encoding was dictated by inter-regional negative alpha-gamma coupling. Our graph filtration over MEG network revealed these inter-regional time-delayed cross-frequency connectivity serve gating of memory encoding